Electric energy is supposed to be consumed right after it has been generated, because it is very difficult and expensive to store.
There is a substantial difference between the amount of electric energy consumed at day and that of at night, and the nighttime residual electric power needs to be converted to and stored in another form of energy which is to be consumed in daytime in order to improve the efficiency of energy consumption.
To fulfill the above-mentioned need, a heat accumulation system, which can store the nighttime residual electric power as cooling energy, has been developed, and introduction of this heat accumulation system can contribute to stabilization of the nationwide power demand and reduce the cost of cooling down a building.
Heat accumulation systems for storing latent heat of vaporization can be divided into those having a heat accumulator in charge of only a part of the cooling load necessary for a day (partial heat accumulation type), and those having a heat accumulator in charge of the whole daily cooling load (whole heat accumulation type).
Because the whole heat accumulation type needs to store more cooling energy, bigger coolers and more space are required compared to the partial heat accumulation type. For this reason, the partial heat accumulation type is preferred to be adopted and widely used in Korea.
Nevertheless, the partial heat accumulation type still requires a well-combined operation of coolers and accumulators according to the cooling load so that high efficiency of energy consumption can be achieved.
However, operation of the systems has entirely been dependent on the operator's experience for years. This means that, in many cases, the operator's misjudgment and inexperienced operation have wasted power and increased the operating cost. Furthermore, insufficient supply of cooling has frequently caused inconveniences and complaints of the users.
Because heat accumulation systems store the cooling energy, which is necessary during the daytime, in advance (i.e. at midnight), an accurate prediction for how much cooling energy (so called “cooling load”) is needed during the daytime is indispensable. For this reason, many cooling load prediction techniques have been studied and developed.
Researches regarding the cooling load prediction for more effective operation of heat accumulation systems have mainly been conducted in Japan, which adopts a midnight electric power billing system as in the case of Korea.
Tadahiko et al. have combined a TBCM model, which is based on topology, with an ARIMA model, which is based on time-series statistics, to obtain a hybrid model, and predict the cooling load through the curve of the hybrid model. Harunori et al. have proposed a technique for predicting the cooling load based on an ARX model. Jin et al. have proposed a cooling load prediction technique, which employs an adaptive neural network to consider even unpredicted load fluctuation among input data. Nobuo et al. have compared cooling load prediction results obtained by employing the Kalman filter model, GMDH model, and neural network model to benchmarked buildings and offices in order to verify the relative prediction accuracy.
Because all of the above-mentioned prediction techniques are based on complicated mathematical and/or statistical methods, the operators without professional knowledge have difficulty in using the techniques. In addition, above techniques heavily rely on past operation data regarding the building, to which cooling load prediction is to be applied. This means that, if a building has insufficient past operation data, the above methods can hardly be applied.